Customers purchase casualty insurance policies to insulate themselves from various risks posed to their property. For example, a homeowner may purchase a fire insurance policy or a driver may purchase an automobile insurance policy. Various “loss events” can result in damage to this property which can lead to customers filing insurance claims for the damage to collect any monies owed according to the casualty insurance policy. For example, loss events can result from hurricanes, earthquakes, severe storms, tornados, hail storms, wildfires, and other causes. Generally, insurance providers have access to historical data that can comprise information such as the costs of property damage, the number of claims filed and percentages associated therewith, the amount of resources (e.g., claim representatives, computing resources) needed to manage insurance processing resulting from the loss events, amounts of specific parts or supplies that were required to repair damage, and other data. This historical data can assist insurance providers to adequately plan for a certain amount of resources to respond to insurance claims resulting from loss events.
However, each loss event results in varying or different amounts of damages and associated costs. For example, a “category 3” hurricane that hits a densely populated area on the East coast may cause more damage than a similar-scale “category 3” hurricane that impacts a sparsely populated area on the Gulf of Mexico. In the case of an approaching, currently-occurring, or recently-occurred storm or other loss event trigger, the historical data may not accurately account for an actual amount of damage or expected amount of damage. Therefore, the amount or level of resources that insurance providers plan for can often be insufficient or, in some cases, more than necessary.
Accordingly, there is an opportunity for systems and methods to more effectively and efficiently allocate or schedule resources used in managing insurance processing associated with loss events.